1. Field of the Invention
The present invention relates to an object detection control apparatus, and, more particularly to an object detection control apparatus, an object detecting system, and a control method therefor for detecting an object in an image with parallel processing and a computer program for causing a computer to execute the method.
2. Description of the Related Art
In the past, as a method of detecting an object such as a face included in an input image, for example, there is known a template matching method for collating plural reduced images hierarchically generated with respect to the input image and a template image of the object to specify the object. In the template matching method, it is a general practice to perform object detection processing while scanning the template image from the left to right in the horizontal direction with respect to the input image and the plural reduced images. However, in this method, correlation values and differential root sum values are often used and processing for using the values takes time. Therefore, for example, there is proposed a method of reducing the number of hierarchically-generated reduced images to improve the speed of face detection processing (see, for example, JP-A-2007-265390). A generally-used method for face detection processing is briefly explained with reference to drawings.
FIGS. 20A to 20C are schematic diagrams of the method for face detection processing. In FIGS. 20A to 20C, an input image 810 and reduced images 820 and 830, which are face detection targets, and face detection areas 811, 821 and 831 are shown. In order to detect faces of different sizes included in the input image 810, the size of a template image is fixed and the reduced images 820 and 830 obtained by hierarchically reducing the size of the input image are generated to perform the face detection processing. A reduction ratio for generating reduced images is set to 0.7. The face detection areas 811, 821, and 831 are areas in which the face detection processing is performed. The width of the face detection areas 811, 821, and 831 is set to 20 pixels and the height thereof is set to the height of the detection target input image 810 or reduced images 820 to 830.
In FIG. 20A, the face detection processing is performed while the face detection area 811 having the size of 960 pixels in height and 20 pixels in width is moved from the left to right with respect to the input image 810 having the size of 960 pixels in height and 1280 pixels in width. In this case, after the template image is moved from up to down in the face detection area 811, the face detection area 811 is moved in the right direction. When the face detection processing for the input image 810 is finished, as shown in FIG. 20B, the reduced image 820 obtained by multiplying the height and the width of the input image 810 by 0.7 is generated and the face detection processing is performed while the face detection area 821 is moved from the left to right as explained above. The width of the face detection area 821 is 20 pixels and is the same as the width of the face detection area 811. However, the height of the face detection area 821 is set to the height of the reduced image 820. When the face detection processing for the reduced image 820 is finished, the reduced image 820 is further reduced according to a reduction ratio. Finally, the processing is repeated until the reduced image 820 is reduced to the size of the reduced image 830 shown in FIG. 20C. Transition of the face detection area moved from the left to right is briefly explained below.
FIGS. 21A to 21C are schematic diagrams of a method of the face detection processing for the input image 810. In FIGS. 21A to 21C, an example of transition of the face detection area 811 with respect to the input image 810 is shown. In FIG. 21A, zeroth to nineteenth rows of the input image 810 are allocated as the face detection area 811. When the face detection processing in this position is finished, as shown in FIG. 21B, the face detection area 811 (second to twenty-first rows of the input image 810) formed by moving the face detection area 811 in the right direction by two pixels is allocated anew and the face detection processing is performed. Subsequently, as shown in FIG. 21C, the face detection area 811 is further moved in the right direction by two pixels and the face detection processing is performed. The same processing is repeated to the right end of the input image 810.
In this way, the reduced image areas are hierarchically generated and the face detection area is scanned from the left to right in the horizontal direction with respect to the reduced images to perform the face detection processing. In general, such face detection processing is executed by one processor.